深空通信中利用GEO卫星的双跳下行链路特性研究

利用现有的地球静止轨道(GEO)卫星资源,构建深空通信中深空探测器到GEO卫星、再到地面站的双跳链路系统。在自由空间链路段载波宜采用较高频率以获得链路增益;在GEO卫星到地面站链路段宜采用10GHz左右的卫星通信窗口以规避大气的相关影响。与传统一跳链路相比,双跳链路系统可以获得更大的信噪比和信道容量,以及更小的误码率。采用现有的GEO地面天线完全能够满足深空通信的要求,提高了系统的可靠性。     

粉末烧结Nd15Fe77B8永磁合金的矫顽力特征

通过测量粉末烧结Ｎｄ１５Ｆ３７７Ｂ８永磁合金的充磁和退磁曲线，结合金相组织及磁畴观察分析，证明该合金的矫顽力是由畴壁的钉扎来控制。     

DID检测器气相色谱仪用于稀有气体分析

叙述了DID检测器应用于稀有气体分析,以增加电场梯度方式提高氦中氖的检测灵敏度.     

The Deep Impact Earth-Based Campaign

Prior to the selection of the comet 9P/Tempel 1 as the Deep Impact mission target, the comet was not well observed. From 1999 through the present there has been an intensive world-wide observing campaign designed to obtain mission critical information about the target nucleus, including the nucleus size, albedo, rotation rate, rotation state, phase function, and the development of the dust and gas coma. The specific observing schemes used to obtain this information and the resources needed are presented here. The Deep Impact mission is unique in that part of the mission observations will rely on an Earth-based (ground and orbital) suite of complementary observations of the comet just prior to impact and in the weeks following. While the impact should result in new cometary activity, the actual physical outcome is uncertain, and the Earth-based observations must allow for a wide range of post-impact phenomena. A world-wide coordinated effort for these observations is described.     

LEO卫星网络的切换策略及性能分析

采用Dijkstra算法,分析了低轨(LEO)卫星网络的距离最短、时延最小、跳数最小、持续时间最长等典型路由切换策略,并比较了性能。在综合考虑切换性能和时延等指标的基础上,提出了一种持续时间最长和时延最小组合,以及完全路由重构与部分路由重构结合的混合切换策略。各切换策略性能比较的结果表明,该混合切换策略的性能较优。     

稀土化合物对硅橡胶包覆材料粘接性能影响的研究

研究了氧化镧、草酸铈和铬酸镧三种稀土化合物对双组分缩合型室温硫化(RTV)硅橡胶包覆材料粘接性能的影响。发现稀土化合物确实能提高硅橡胶与刷涂底漆的HMX—CMDB推进剂或Al—RDX—CMDB推进剂之间的粘接强度,并且硅橡胶与HMX—CMDB推进剂粘接的剪切破坏形式为硅橡胶本身的内聚破坏。     

卫星通信设备自动化测试系统的应用

介绍了卫星地面站通信设备自动化测试系统的组成、工作原理及系统测试项目。系统采用计算机、测试仪器与 GPIB协议 ,实现了卫星通信设备测试工作的自动化 ,并可代替以往人工的测试手段。该系统已在某卫星地面站测试工作中得到应用。     

铸钢用泡沫陶瓷过滤器的研制

部分稳定氧化锆(PSZ)质泡沫陶瓷过滤器是用于高温合金及铸钢金属液净化的一种性能最为理想的过滤材料。以Mg-PSZ为骨料,CeO2、富铈稀土为添加剂制备的泡沫陶瓷过滤器具有较好的高温性能。在利用扫描电镜、X衍射仪对泡沫陶瓷过滤器晶相及组织形貌进行分析的基础上,文章就部分稳定氧化锆中稳定相对高温性能的影响进行了较深入的探讨。     

Debris flux comparisons from the Goldstone Radar,Haystack Radar,and Hax Radar prior,during, and after the last solar maximum

The continual monitoring of the low Earth orbit (LEO) debris environment using highly sensitive radars is essential for an accurate characterization of these dynamic populations. Debris populations are continually evolving since there are new debris sources, previously unrecognized debris sources, and debris loss mechanisms that are dependent on the dynamic space environment. Such radar data are used to supplement, update, and validate existing orbital debris models. NASA has been utilizing radar observations of the debris environment for over a decade from three complementary radars: the NASA JPL Goldstone radar, the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar), and the MIT/LL Haystack Auxiliary radar (HAX). All of these systems are highly sensitive radars that operate in a fixed staring mode to statistically sample orbital debris in the LEO environment. Each of these radars is ideally suited to measure debris within a specific size region. The Goldstone radar generally observes objects with sizes from 2 mm to 1 cm. The Haystack radar generally measures from 5 mm to several meters. The HAX radar generally measures from 2 cm to several meters. These overlapping size regions allow a continuous measurement of cumulative debris flux versus diameter from 2 mm to several meters for a given altitude window. This is demonstrated for all three radars by comparing the debris flux versus diameter over 200 km altitude windows for 3 nonconsecutive years from 1998 to 2003. These years correspond to periods before, during, and after the peak of the last solar cycle. Comparing the year to year flux from Haystack for each of these altitude regions indicate statistically significant changes in subsets of the debris populations. Potential causes of these changes are discussed. These analysis results include error bars that represent statistical sampling errors.